import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static < T extends RealType< T > & NativeType< T >> void main( final String[] args )
{
	ImageJ.main( args );
	final File file = new File( "DrosophilaWing.tif" );
	final ImagePlus imp = IJ.openImage( file.getAbsolutePath() );
	final Img< T > img = ImagePlusAdapter.wrap( imp );

	final long start = System.currentTimeMillis();

	final Shape shape = new DiamondTipsShape( 10 );
	final Img< T > target = Dilation.dilate( img, shape, 1 );

	final long end = System.currentTimeMillis();

	System.out.println( "Processing done in " + ( end - start ) + " ms." );

	ImageJFunctions.show( img );
	ImageJFunctions.show( target );

}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void main( String[] args )
	{
		String srcImgFn = "/groups/jain/home/bogovicj/learning/advanced-imglib2/images/bee-1.tif";
		Img<FloatType> img =  ImagePlusAdapter.convertFloat( IJ.openImage(srcImgFn) );
	
		int[] sz = new int[]{ (int)img.dimension(0), (int)img.dimension(1) };
		Img<FloatType> img2 = ImgOps.createGradientImgX( sz, new FloatType());			

		//imageStats( img );
		//imageTextureStats( img );
	
		// function that normalizes to range [0,1] 
//		Normalize<FloatType> nrmFun = new Normalize<FloatType>( 
//			0, 255, 0, 1);	
//		evalFun( img, nrmFun );

		// add the images
		RealAdd<FloatType,FloatType,FloatType> sumfun = new RealAdd<FloatType,FloatType,FloatType>();
		evalFun( img, img2, sumfun );

		System.out.println("finished");
		System.exit(0);
	}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void tryMatchRegistration() 
	{
		String imgfn = "/data-ssd1/john/projects/crackSegmentation/crackVolDown_cp.tif";
		String maskfn = "/data-ssd1/john/projects/crackSegmentation/Labels_ds_interp_cp_smooth.tif";
		int[] patchSize = new int[] { 19, 19, 7 };
		
		Img<FloatType> img =  ImagePlusAdapter.convertFloat( IJ.openImage(imgfn) );
		Img<FloatType> mask = ImagePlusAdapter.convertFloat( IJ.openImage(maskfn) );

		CrackCorrection<FloatType> cc = new CrackCorrection<FloatType>(
				img, mask, patchSize);
		cc.computeEdgels();
		
		int i = cc.edgelIdxNearest(new double[]{67,290,13});
		int j = cc.edgelIdxNearest(new double[]{69,311,13});
		
		System.out.println(" i: " + i + "  " + cc.getEdgels().get(i));
		System.out.println(" j: " + j + "  " + cc.getEdgels().get(j));
	
		cc.debugOutDir = "/data-ssd1/john/projects/crackPatching/edgelRegPatch";
//		cc.registerEdgelsOrient( cc.getEdgels().get(i), cc.getEdgels().get(j), i);
		
	}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static FloatImagePlus< net.imglib2.type.numeric.real.FloatType > createImgLib2( final List< float[] > img, final int w, final int h )
{
	final ImagePlus imp;

	if ( img.size() > 1 )
	{
		final ImageStack stack = new ImageStack( w, h );
		for ( int z = 0; z < img.size(); ++z )
			stack.addSlice( new FloatProcessor( w, h, img.get( z ) ) );
		imp = new ImagePlus( "ImgLib2 FloatImagePlus (3d)", stack );
	}
	else
	{
		imp = new ImagePlus( "ImgLib2 FloatImagePlus (2d)", new FloatProcessor( w, h, img.get( 0 ) ) );
	}

	return ImagePlusAdapter.wrapFloat( imp );
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
/**
 * Creates a noisy image that is created by repeatedly adding points
 * with random intensity to the canvas. That way it tries to mimic the
 * way a microscope produces images.
 *
 * @param <T> The wanted output type.
 * @param width The image width.
 * @param height The image height.
 * @param dotSize The size of the dots.
 * @param numDots The number of dots.
 * @param smoothingSigma The two dimensional sigma for smoothing.
 * @return The noise image.
 */
public static <T extends RealType<T> & NativeType<T>> RandomAccessibleInterval<T> produceNoiseImage(int width,
		int height, float dotSize, int numDots) {
	/* For now (probably until ImageJ2 is out) we use an
	 * ImageJ image to draw circles.
	 */
	int options = NewImage.FILL_BLACK + NewImage.CHECK_AVAILABLE_MEMORY;
        ImagePlus img = NewImage.createByteImage("Noise", width, height, 1, options);
	ImageProcessor imp = img.getProcessor();

	float dotRadius = dotSize * 0.5f;
	int dotIntSize = (int) dotSize;

	for (int i=0; i < numDots; i++) {
		int x = (int) (Math.random() * width - dotRadius);
		int y = (int) (Math.random() * height - dotRadius);
		imp.setColor(Color.WHITE);
		imp.fillOval(x, y, dotIntSize, dotIntSize);
	}
	// we changed the data, so update it
	img.updateImage();
	// create the new image
	RandomAccessibleInterval<T> noiseImage = ImagePlusAdapter.wrap(img);

	return noiseImage;
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
/**
 * Creates a mask image with a black background and a white
 * rectangular foreground.
 *
 * @param width The width of the result image.
 * @param height The height of the result image.
 * @param offset The offset of the rectangular mask.
 * @param size The size of the rectangular mask.
 * @return A black image with a white rectangle on it.
 */
public static <T extends RealType<T> & NativeType<T>> RandomAccessibleInterval<T> createRectengularMaskImage(
		long width, long height, long[] offset, long[] size) {
	/* For now (probably until ImageJ2 is out) we use an
	 * ImageJ image to draw lines.
	 */
	int options = NewImage.FILL_BLACK + NewImage.CHECK_AVAILABLE_MEMORY;
        ImagePlus img = NewImage.createByteImage("Noise", (int)width, (int)height, 1, options);
	ImageProcessor imp = img.getProcessor();
	imp.setColor(Color.WHITE);
	Roi rect = new Roi(offset[0], offset[1], size[0], size[1]);

	imp.fill(rect);
	// we changed the data, so update it
	img.updateImage();

	return ImagePlusAdapter.wrap(img);
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
private ByteImagePlus<UnsignedByteType> createImagePlusImage(final ImageProcessor ip) {
	if ( dimensions.length == 1 )
		return null;
	if ( ip != null )
	{
		final ImagePlus imp = new ImagePlus("image", ip);
		return ImagePlusAdapter.wrapByte(imp);
	}
	if ( dimensions[ 0 ] * dimensions[ 1 ] > Integer.MAX_VALUE )
		return null;
	if ( numDimensions > 5 )
		return null;
	final ByteImagePlus<UnsignedByteType> imagePlusContainer = ( ByteImagePlus<UnsignedByteType> ) createImage( dimensions, new ImagePlusImgFactory< UnsignedByteType >() );
	return imagePlusContainer;
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void main( final String[] args )
{
	final int delta = 15;
	final long minSize = 10;
	final long maxSize = 100*100;
	final double maxVar = 0.8;
	final double minDiversity = 0;

	final Img< UnsignedByteType > img;
	try
	{
		new ImageJ();
		IJ.run("Lena (68K)");
		IJ.run("8-bit");
		img = ImagePlusAdapter.wrapByte( IJ.getImage() );
	}
	catch ( final Exception e )
	{
		e.printStackTrace();
		return;
	}

	final ImagePlus impImg = IJ.getImage();
	final ImageStack stack = new ImageStack( (int) img.dimension( 0 ), (int) img.dimension( 1 ) );

	final MserTree< UnsignedByteType > treeDarkToBright = MserTree.buildMserTree( img, new UnsignedByteType( delta ), minSize, maxSize, maxVar, minDiversity, true );
	final MserTree< UnsignedByteType > treeBrightToDark = MserTree.buildMserTree( img, new UnsignedByteType( delta ), minSize, maxSize, maxVar, minDiversity, false );
	final MserTreeExample< UnsignedByteType > vis = new MserTreeExample< UnsignedByteType >( impImg, stack );
	vis.visualise( treeDarkToBright, Color.CYAN );
	vis.visualise( treeBrightToDark, Color.MAGENTA );

	final ImagePlus imp = new ImagePlus("components", stack);
	imp.show();
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static < T extends RealType< T > & NativeType< T >> void main( final String[] args )
{

	ImageJ.main( args );
	final File file = new File( "DrosophilaWing.tif" );
	// final File file = new File(
	// "/Users/JeanYves/Desktop/Data/brightblobs.tif" );
	final ImagePlus imp = IJ.openImage( file.getAbsolutePath() );
	final Img< T > img = ImagePlusAdapter.wrap( imp );

	final long start = System.currentTimeMillis();

	final Shape shape = new PairOfPointsShape( new long[] { -10, 20 } );
	final Img< T > target = Dilation.dilate( img, shape, 1 );

	final long end = System.currentTimeMillis();

	System.out.println( "Processing done in " + ( end - start ) + " ms." );

	ImageJFunctions.show( img );
	ImageJFunctions.show( target );

	final Shape shape2 = new PairOfPointsShape( new long[] { 10, -20 } );
	final Img< T > target2 = Dilation.dilate( img, shape2, 1 );
	ImageJFunctions.show( target2 );

	final Shape shape3 = new PairOfPointsShape( new long[] { 10, 20 } );
	final Img< T > target3 = Dilation.dilate( img, shape3, 1 );
	ImageJFunctions.show( target3 );

}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void testClusteringReal(){
//		String destDir = "/Users/bogovicj/Documents/projects/crackStitching/edgeClustering";
		String destDir = "/groups/saalfeld/home/bogovicj/projects/crackStitching/edgeClustering/closeup";
		
		// load a volume
		int downSampleFactor = 4;
		String imgfn = "/data-ssd1/john/projects/crackSegmentation/groundTruth/closeup/img_ds"+downSampleFactor+".tif";
		String maskfn = "/data-ssd1/john/projects/crackSegmentation/groundTruth/closeup/labels_interp_smooth_ds"+downSampleFactor+".tif";
		Img<FloatType> img =  ImagePlusAdapter.convertFloat( IJ.openImage(imgfn) );
		Img<FloatType> mask = ImagePlusAdapter.convertFloat( IJ.openImage(maskfn) );
		
		// cluster edgels
		int[] patchSize = new int[]{ 9,9 };
		CrackCorrection<FloatType> cc = new CrackCorrection<FloatType>( img, mask, patchSize);
		cc.computeEdgels();
		
		System.out.println(" num edgels - " + cc.getEdgels().size());
		
		EdgelMatching<FloatType> em = new EdgelMatching<FloatType>();
		em.setSearchType( EdgelMatching.SearchTypes.COUNT );
		em.setEdgelSearchCount(27);
		em.setEdgels( cc.getEdgels() );

//		EdgelClustering<FloatType> ec = new EdgelClustering<FloatType>( em );
		EdgelClusteringRansac<FloatType> ec = new EdgelClusteringRansac<FloatType>( em );
		ec.cluster();
		
		Img<FloatType> clusterImg = img.factory().create( img, img.firstElement() );
		ec.makeEdgelClusterImgMem(clusterImg);
		ImgOps.writeFloat( clusterImg, destDir + File.separator + "edgelClusterImg.tif");
		
	}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void test2(){
	String imfn = "/groups/saalfeld/home/bogovicj/tests/testdat/boats.tif";
	Img<FloatType> img =  ImagePlusAdapter.convertFloat( IJ.openImage(imfn) );
	double[] sigmas = new double[]{ 0, 0 };
	double[] dsFactors = new double[]{ 1, 1 };
	
	Img<FloatType> out = Resampling.resampleGaussian(
			img, 
			img.factory(), 
			dsFactors, sigmas, sigmas);
	
	ImgOps.writeFloat( out,  "/groups/saalfeld/home/bogovicj/tests/testdat/boats_myds_1-1.tif");
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
@Override
 public void run(String arg) {
ImagePlus imp1 = IJ.openImage("/Users/dan/Documents/Dresden/ipf/colocPluginDesign/red.tif");
img1 = ImagePlusAdapter.wrap(imp1);
ImagePlus imp2 = IJ.openImage("/Users/dan/Documents/Dresden/ipf/colocPluginDesign/green.tif");
img2 = ImagePlusAdapter.wrap(imp2);

double pearson = calculatePearson();

Img<T> ranImg = generateRandomImageStack(img1, new int[] {2,2,1});
 }
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
/**
 * Creates appropriate data structures from the ROI information
 * passed. If an irregular ROI is found, it will be put into a
 * frame of its bounding box size and put into an {@code Image<T>}.
 *
 * In the end the members ROIs, masks and maskBBs will be
 * filled if ROIs or masks were found. They will be null
 * otherwise.
 */
protected void createMasksAndRois(final Roi[] rois, final int width,
	final int height)
{
	// create empty list
	masks.clear();

	for (final Roi r : rois) {
		final MaskInfo mi = new MaskInfo();
		// add it to the list of masks/ROIs
		masks.add(mi);
		// get the ROIs/masks bounding box
		final Rectangle rect = r.getBounds();
		mi.roi = new BoundingBox(new long[] { rect.x, rect.y }, new long[] {
			rect.width, rect.height });
		final ImageProcessor ipMask = r.getMask();
		// check if we got a regular ROI and return if so
		if (ipMask == null) {
			continue;
		}

		// create a mask processor of the same size as a slice
		final ImageProcessor ipSlice = ipMask.createProcessor(width, height);
		// fill the new slice with black
		ipSlice.setValue(0.0);
		ipSlice.fill();
		// position the mask on the new mask processor
		ipSlice.copyBits(ipMask, (int) mi.roi.offset[0], (int) mi.roi.offset[1],
			Blitter.COPY);
		// create an Image<T> out of it
		final ImagePlus maskImp = new ImagePlus("Mask", ipSlice);
		// and remember it and the masks bounding box
		mi.mask = ImagePlusAdapter.<T> wrap(maskImp);
	}
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
/**
 * This method creates a noise image that is made of many little
 * sticks oriented in a random direction. How many of them and
 * what the length of them are can be specified.
 *
 * @return a new noise image that is not smoothed
 */
public static <T extends RealType<T> & NativeType<T>> RandomAccessibleInterval<T> produceSticksNoiseImage(int width,
		int height, int numSticks, int lineWidth, double maxLength) {
	/* For now (probably until ImageJ2 is out) we use an
	 * ImageJ image to draw lines.
	 */
	int options = NewImage.FILL_BLACK + NewImage.CHECK_AVAILABLE_MEMORY;
        ImagePlus img = NewImage.createByteImage("Noise", width, height, 1, options);
	ImageProcessor imp = img.getProcessor();
	imp.setColor(Color.WHITE);
	imp.setLineWidth(lineWidth);

	for (int i=0; i < numSticks; i++) {
		// find random starting point
		int x = (int) (Math.random() * width);
		int y = (int) (Math.random() * height);
		// create random stick length and direction
		double length = Math.random() * maxLength;
		double angle = Math.random() * 2 * Math.PI;
		// calculate random point on circle, for the direction
		int destX = x + (int) (length * Math.cos(angle));
		int destY = y + (int) (length * Math.sin(angle));
		// now draw the line
		imp.drawLine(x, y, destX, destY);
	}
	// we changed the data, so update it
	img.updateImage();

	return ImagePlusAdapter.wrap(img);
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
/** Wrap an ImageJ's {@link ImagePlus} as an Imglib {@link Img} of the appropriate type.
 * The data is not copied, but merely accessed with a PlanarArrayContainer.
 * @see ImagePlusAdapter */
public static<T extends RealType<T> & NativeType<T>> Img<T> wrap(final ImagePlus imp) {
	return ImagePlusAdapter.<T>wrap(imp);
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
private Img<UnsignedByteType> createImagePlusImage(final ImageProcessor ip) {
	final ImagePlus imp = new ImagePlus("image", ip);
	return ImagePlusAdapter.wrapByte(imp);
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static <T extends RealType<T> & NativeType<T>> void main(final String[] args) {

		ImageJ.main(args);
		final File file = new File( "DrosophilaWing.tif" );
		final ImagePlus imp = IJ.openImage(file.getAbsolutePath());
		final Img<T> img = ImagePlusAdapter.wrap(imp);

		final long start = System.currentTimeMillis();

		final Shape shape = new PeriodicLineShape(2, new int[] { 20, -15 });
		final Img< T > target = Erosion.erode( img, shape, 1 );

		final long end = System.currentTimeMillis();

		System.out.println( "Processing done in " + ( end - start ) + " ms." );

		ImageJFunctions.show(img);
		ImageJFunctions.show(target);

	}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public Img<UnsignedByteType> getDirectionImage(ImagePlus img)
{
	float[][] kirsch = new float[][] { {-3,-3,5,-3,0,5,-3,-3,5},
					   {-3,5,5,-3,0,5,-3,-3,-3},
				   	   {5,5,5,-3,0,-3,-3,-3,-3},					   	   
				   	   {5,5,-3,5,0,-3,-3,-3,-3},					   	   
				   	   {5,-3,-3,5,0,-3,5,-3,-3},					   	   
				   	   {-3,-3,-3,5,0,-3,5,5,-3},					   	   
				   	   {-3,-3,-3,-3,0,-3,5,5,5},					   	   
				   	   {-3,-3,-3,-3,0,5,-3,5,5}};


	Img<UnsignedByteType>[] responseImages = new Img[8];

	for(int i = 0; i < 8; i++)
	{
		ImagePlus tmp = img.duplicate();
		tmp.getChannelProcessor().convolve(kirsch[i],3,3);
		responseImages[i] = ImagePlusAdapter.wrap(tmp);
	}

	Cursor c1 = responseImages[0].cursor();
	Cursor c2 = responseImages[1].cursor();
	Cursor c3 = responseImages[2].cursor();
	Cursor c4 = responseImages[3].cursor();
	Cursor c5 = responseImages[4].cursor();
	Cursor c6 = responseImages[5].cursor();
	Cursor c7 = responseImages[6].cursor();
	Cursor c8 = responseImages[7].cursor();



	long[] dim = new long[2];
	responseImages[0].dimensions(dim);
	
	//final Img< T > directionImage = imgFactory.create( responseImages[0], responseImages[0].firstElement() );

	ImgFactory< UnsignedByteType > imgFactory = new ArrayImgFactory< UnsignedByteType >();
	final Img<UnsignedByteType> directionImage = imgFactory.create(dim,new UnsignedByteType());
	//final Img< T > directionImage = imgFactory.create(dim,new RealType());
	
	Cursor<UnsignedByteType> cDirection = directionImage.cursor();
	
	while (c1.hasNext())
	{
		RealType[] t = new RealType[8]; 
		t[0] = (RealType)c1.next();
		t[1] = (RealType)c2.next();
		t[2] = (RealType)c3.next();
		t[3] = (RealType)c4.next();
		t[4] = (RealType)c5.next();
		t[5] = (RealType)c6.next();
		t[6] = (RealType)c7.next();
		t[7] = (RealType)c8.next();

		RealType tDirection = cDirection.next();

		float max = 0f;
		int kernelId = 0;
		for(int i = 0; i < 8; i++)
		{
			float currentValue = t[i].getRealFloat();
			if(i==0) 
			{
				max = currentValue;
				kernelId = 0;
			}
			else if(currentValue>max) 
			{
				max = currentValue;
				kernelId = i;
			}
		}

		tDirection.setReal(kernelId);
		
	}

	return directionImage;
}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void main(String[] args) {
		
		int downSampleFactor = 4;
//		double searchRadius = 100;
		int    searchCount  = 60;
		
		String imgfn = "/data-ssd1/john/projects/crackSegmentation/groundTruth/closeup/img_ds"+downSampleFactor+".tif";
		String maskfn = "/data-ssd1/john/projects/crackSegmentation/groundTruth/closeup/labels_interp_smooth_ds"+downSampleFactor+".tif";
		Img<FloatType> img =  ImagePlusAdapter.convertFloat( IJ.openImage(imgfn) );
		Img<FloatType> mask = ImagePlusAdapter.convertFloat( IJ.openImage(maskfn) );
		
//		int[] patchSize = new int[] { 45, 45, 19 };
		int[] patchSize = new int[] { 31, 31, 19 };
//		int[] patchSize = new int[] { 15, 15, 13 };
		
		CrackCorrection<FloatType> cc = new CrackCorrection<FloatType>(
				img, mask, patchSize);
		
		EdgelMatching<FloatType> em = new EdgelMatching<FloatType>(img, mask, patchSize);
		em.debugDir = "/data-ssd1/john/projects/crackPatching/cropEdgelMatch";
		em.debugSuffix = "ds"+downSampleFactor;
		
		em.setSearchType( EdgelMatching.SearchTypes.COUNT );
		em.setEdgelSearchCount( searchCount );
		
//		em.setEdgelSearchRadius( searchRadius / (downSampleFactor) );
		
		cc.edgelMatcher = em;
		
		cc.computeEdgels();
		cc.edgelMatcher.setEdgels(cc.getEdgels());
		
		EdgelClusteringRansac<FloatType> ec = new EdgelClusteringRansac<FloatType>(
			cc.edgelMatcher);
		
		ec.cluster( );
		
		Img<FloatType> clusterImg = img.factory().create( img, img.firstElement());
//		ec.makeEdgelClusterImg( clusterImg );
		ec.makeEdgelClusterImgMem( clusterImg );
		
		Format formatter = new SimpleDateFormat("yyyyMMdd-HHmmss");
		String dtstr = formatter.format(Calendar.getInstance().getTime());
		String fn = String.format("/groups/saalfeld/home/bogovicj/tmp/edgelClustersMemRansac_%s.tif", dtstr);
		logger.info("fn: " + fn);
		ImgOps.writeFloat( clusterImg, fn);
		
		
		logger.info("finished");
		System.exit(0);
	}
 

import net.imglib2.img.ImagePlusAdapter; //导入依赖的package包/类
public static void main(String[] args) {
		
		int downSampleFactor = 4;
//		double searchRadius = 100;
		int    searchCount  = 60;
		
		String imgfn = "/data-ssd1/john/projects/crackSegmentation/groundTruth/closeup/img_ds"+downSampleFactor+".tif";
		String maskfn = "/data-ssd1/john/projects/crackSegmentation/groundTruth/closeup/labels_interp_smooth_ds"+downSampleFactor+".tif";
		Img<FloatType> img =  ImagePlusAdapter.convertFloat( IJ.openImage(imgfn) );
		Img<FloatType> mask = ImagePlusAdapter.convertFloat( IJ.openImage(maskfn) );
		
//		int[] patchSize = new int[] { 45, 45, 19 };
		int[] patchSize = new int[] { 31, 31, 19 };
//		int[] patchSize = new int[] { 15, 15, 13 };
		
		CrackCorrection<FloatType> cc = new CrackCorrection<FloatType>(
				img, mask, patchSize);
		
		EdgelMatching<FloatType> em = new EdgelMatching<FloatType>(img, mask, patchSize);
		em.debugDir = "/data-ssd1/john/projects/crackPatching/cropEdgelMatch";
		em.debugSuffix = "ds"+downSampleFactor;
		
		em.setSearchType( EdgelMatching.SearchTypes.COUNT );
		em.setEdgelSearchCount( searchCount );
		
//		em.setEdgelSearchRadius( searchRadius / (downSampleFactor) );
		
		cc.edgelMatcher = em;
		
		cc.computeEdgels();
		cc.edgelMatcher.setEdgels(cc.getEdgels());
		
		EdgelClustering<FloatType> ec = 
				new EdgelClustering<FloatType>(
						cc.edgelMatcher);
		
		ec.cluster( );
		Img<FloatType> clusterImg = img.factory().create( img, img.firstElement());
//		ec.makeEdgelClusterImg( clusterImg );
		ec.makeEdgelClusterImgMem( clusterImg );
		
		Format formatter = new SimpleDateFormat("yyyyMMdd-HHmmss");
		String dtstr = formatter.format(Calendar.getInstance().getTime());
		String fn = String.format("/groups/saalfeld/home/bogovicj/tmp/edgelClustersMem_%s.tif", dtstr);
		logger.info("fn: " + fn);
		ImgOps.writeFloat( clusterImg, fn);
		
		
		/* CHECK CONFLICT CONDITION METHOD */
//		System.out.println( "A A S :"  + isConflict( CLASSA, CLASSA, true));
//		System.out.println( "A B S :"  + isConflict( CLASSA, CLASSB, true));
//		System.out.println( "A A D :"  + isConflict( CLASSA, CLASSA, false));
//		System.out.println( "A B D :"  + isConflict( CLASSA, CLASSB, false));
		
		
		logger.info("finished");
		System.exit(0);
	}